Dograh vs Moshi

Detailed side-by-side comparison to help you choose the right tool

Dograh

🔴Developer

Voice AI

Open-source, self-hostable voice agent platform — the Vapi and Retell alternative driven by MCP.

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Starting Price

🔴Developer

Voice AI

Open-source real-time conversational AI by Kyutai — a full-duplex voice assistant that can listen and speak simultaneously with low latency.

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Starting Price

Free

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Feature	Dograh	Moshi
Category	Voice AI	Voice AI
Pricing Plans	3 listed plans	2 listed plans
Starting Price	$0	Free
Key Features	• Open-source, self-hostable voice agent stack • MCP-native — drive the agent from any MCP host • Swappable STT, LLM, TTS and telephony providers	• Full-duplex real-time conversation with ~200ms latency • End-to-end speech model — no separate STT/LLM/TTS pipeline • 70 emotional and speaking styles with natural prosody

✓True self-hosting clears compliance bars that exclude closed-cloud voice vendors
✓MCP-native design composes with any existing agent runtime without prompt rewrites
✓Every layer (STT, LLM, TTS, telephony) is swappable — no vendor lock-in
✓Free open-source tier means you can prototype without procurement

✗You take on the operational burden of running Docker, secrets, telephony, monitoring
✗Visual editor less polished than closed competitors like Vapi or Retell
✗Smaller community than the managed cloud vendors — fewer answers when stuck
✗Per-minute STT/TTS/LLM/telephony costs still apply and dominate at scale

✓True full-duplex conversation is a genuine technical breakthrough — most voice AI can't do this
✓200ms latency makes conversations feel human-natural
✓Fully open-source with model weights, so you own your deployment
✓Can run locally for complete privacy — no data leaves your machine
✓70 speaking styles give real emotional range, not flat monotone
✓No per-minute API fees when self-hosted

✗Requires an L4 GPU or similar for good performance — not trivial to self-host
✗Smaller community and ecosystem compared to ElevenLabs or OpenAI voice offerings
✗Fine-tuning for custom voices or domains requires ML expertise
✗Multi-language support exists but quality varies by language
✗Production deployment requires significant infrastructure knowledge
✗API pricing and availability details are limited

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